# IEEE Transactions on Cybernetics

## Filter Results

Displaying Results 1 - 24 of 24
• ### Table of contents

Publication Year: 2014, Page(s): C1
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• ### IEEE Transactions on Cybernetics publication information

Publication Year: 2014, Page(s): C2
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• ### Semi-Supervised Linear Discriminant Clustering

Publication Year: 2014, Page(s):989 - 1000
Cited by:  Papers (12)
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This paper devises a semi-supervised learning method called semi-supervised linear discriminant clustering (Semi-LDC). The proposed algorithm considers clustering and dimensionality reduction simultaneously by connecting K-means and linear discriminant analysis (LDA). The goal is to find a feature space where the K-means can perform well in the new space. To exploit the information brought by unla... View full abstract»

• ### From Heuristic Optimization to Dictionary Learning: A Review and Comprehensive Comparison of Image Denoising Algorithms

Publication Year: 2014, Page(s):1001 - 1013
Cited by:  Papers (139)
| | PDF (12238 KB) | HTML

Image denoising is a well explored topic in the field of image processing. In the past several decades, the progress made in image denoising has benefited from the improved modeling of natural images. In this paper, we introduce a new taxonomy based on image representations for a better understanding of state-of-the-art image denoising techniques. Within each category, several representative algor... View full abstract»

• ### NATAS: Neural Activity Trace Aware Saliency

Publication Year: 2014, Page(s):1014 - 1024
Cited by:  Papers (2)
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Saliency detection has raised much interest in computer vision recently. Many visual saliency models have been developed for individual images, video clips, and image pairs. However, image sequence, one most general occasion in the real world, is not explored yet. A general image sequence is different from video clips whose temporal continuity is maintained and image pairs where common objects exi... View full abstract»

• ### Mathematical Biodynamic Feedthrough Model Applied to Rotorcraft

Publication Year: 2014, Page(s):1025 - 1038
Cited by:  Papers (5)
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Biodynamic feedthrough (BDFT) occurs when vehicle accelerations feed through the human body and cause involuntary control inputs. This paper proposes a model to quantitatively predict this effect in rotorcraft. This mathematical BDFT model aims to fill the gap between the currently existing black box BDFT models and physical BDFT models. The model structure was systematically constructed using asy... View full abstract»

• ### Social Voting Advice Applications—Definitions, Challenges, Datasets and Evaluation

Publication Year: 2014, Page(s):1039 - 1052
Cited by:  Papers (18)
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Voting advice applications (VAAs) are online tools that have become increasingly popular and purportedly aid users in deciding which party/candidate to vote for during an election. In this paper we present an innovation to current VAA design which is based on the introduction of a social network element. We refer to this new type of online tool as a social voting advice application (SVAA). SVAAs e... View full abstract»

• ### Exemplar-Based Human Action Pose Correction

Publication Year: 2014, Page(s):1053 - 1066
Cited by:  Papers (11)
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The launch of Xbox Kinect has built a very successful computer vision product and made a big impact on the gaming industry. This sheds lights onto a wide variety of potential applications related to action recognition. The accurate estimation of human poses from the depth image is universally a critical step. However, existing pose estimation systems exhibit failures when facing severe occlusion. ... View full abstract»

• ### Nonparallel Support Vector Machines for Pattern Classification

Publication Year: 2014, Page(s):1067 - 1079
Cited by:  Papers (83)
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We propose a novel nonparallel classifier, called nonparallel support vector machine (NPSVM), for binary classification. Our NPSVM that is fully different from the existing nonparallel classifiers, such as the generalized eigenvalue proximal support vector machine (GEPSVM) and the twin support vector machine (TWSVM), has several incomparable advantages: (1) two primal problems are constructed impl... View full abstract»

• ### Differential Evolution With Two-Level Parameter Adaptation

Publication Year: 2014, Page(s):1080 - 1099
Cited by:  Papers (71)
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The performance of differential evolution (DE) largely depends on its mutation strategy and control parameters. In this paper, we propose an adaptive DE (ADE) algorithm with a new mutation strategy DE/lbest/1 and a two-level adaptive parameter control scheme. The DE/lbest/1 strategy is a variant of the greedy DE/best/1 strategy. However, the population is mutated under the guide of multiple locall... View full abstract»

• ### Robust Mixed$l_{1}/H_{\infty}$Filtering for Affine Fuzzy Systems With Measurement Errors

Publication Year: 2014, Page(s):1100 - 1110
Cited by:  Papers (18)
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This paper investigates the robust filtering problem for a class of nonlinear systems described by affine fuzzy parts with norm-bounded uncertainties. The system outputs are chosen as the premise variables of fuzzy models, and their measured values are chosen as the premise variables and inputs of fuzzy filters. The measurement errors between the outputs of the plant and the inputs of the filter a... View full abstract»

• ### Fuzzy Sampled-Data Control for Uncertain Vehicle Suspension Systems

Publication Year: 2014, Page(s):1111 - 1126
Cited by:  Papers (140)
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This paper investigates the problem of sampled-data H∞control of uncertain active suspension systems via fuzzy control approach. Our work focuses on designing state-feedback and output-feedback sampled-data controllers to guarantee the resulting closed-loop dynamical systems to be asymptotically stable and satisfy H∞disturbance attenuation level and suspension performance con... View full abstract»

• ### A Scatter Learning Particle Swarm Optimization Algorithm for Multimodal Problems

Publication Year: 2014, Page(s):1127 - 1140
Cited by:  Papers (31)
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Particle swarm optimization (PSO) has been proved to be an effective tool for function optimization. Its performance depends heavily on the characteristics of the employed exemplars. This necessitates considering both the fitness and the distribution of exemplars in designing PSO algorithms. Following this idea, we propose a novel PSO variant, called scatter learning PSO algorithm (SLPSOA) for mul... View full abstract»

• ### A Biodynamic Feedthrough Model Based on Neuromuscular Principles

Publication Year: 2014, Page(s):1141 - 1154
Cited by:  Papers (5)
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A biodynamic feedthrough (BDFT) model is proposed that describes how vehicle accelerations feed through the human body, causing involuntary limb motions and so involuntary control inputs. BDFT dynamics strongly depend on limb dynamics, which can vary between persons (between-subject variability), but also within one person over time, e.g., due to the control task performed (within-subject variabil... View full abstract»

• ### Takagi–Sugeno Model Based Analysis of EWMA RtR Control of Batch Processes With Stochastic Metrology Delay and Mixed Products

Publication Year: 2014, Page(s):1155 - 1168
Cited by:  Papers (5)
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In many batch-based industrial manufacturing processes, feedback run-to-run control is used to improve production quality. However, measurements may be expensive and cannot always be performed online. Thus, the measurement delay always exists. The metrology delay will affect the stability and performance of the process. Moreover, since quality measurements are performed offline, delay is not fixed... View full abstract»

• ### Machine Learning Source Separation Using Maximum a Posteriori Nonnegative Matrix Factorization

Publication Year: 2014, Page(s):1169 - 1179
Cited by:  Papers (15)
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A novel unsupervised machine learning algorithm for single channel source separation is presented. The proposed method is based on nonnegative matrix factorization, which is optimized under the framework of maximum a posteriori probability and Itakura-Saito divergence. The method enables a generalized criterion for variable sparseness to be imposed onto the solution and prior information to be exp... View full abstract»

• ### Spectral Embedded Hashing for Scalable Image Retrieval

Publication Year: 2014, Page(s):1180 - 1190
Cited by:  Papers (30)
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We propose a new graph based hashing method called spectral embedded hashing (SEH) for large-scale image retrieval. We first introduce a new regularizer into the objective function of the recent work spectral hashing to control the mismatch between the resultant hamming embedding and the low-dimensional data representation, which is obtained by using a linear regression function. This linear regre... View full abstract»

• ### Triplex Transfer Learning: Exploiting Both Shared and Distinct Concepts for Text Classification

Publication Year: 2014, Page(s):1191 - 1203
Cited by:  Papers (7)
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Transfer learning focuses on the learning scenarios when the test data from target domains and the training data from source domains are drawn from similar but different data distributions with respect to the raw features. Along this line, some recent studies revealed that the high-level concepts, such as word clusters, could help model the differences of data distributions, and thus are more appr... View full abstract»

• ### SOS Based Robust${\cal H}_{\infty}$Fuzzy Dynamic Output Feedback Control of Nonlinear Networked Control Systems

Publication Year: 2014, Page(s):1204 - 1213
Cited by:  Papers (47)
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In this paper, a methodology for designing a fuzzy dynamic output feedback controller for discrete-time nonlinear networked control systems is presented where the nonlinear plant is modelled by a Takagi-Sugeno fuzzy model and the network-induced delays by a finite state Markov process. The transition probability matrix for the Markov process is allowed to be partially known, providing a more pract... View full abstract»

• ### Constrained Concept Factorization for Image Representation

Publication Year: 2014, Page(s):1214 - 1224
Cited by:  Papers (20)
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Matrix factorization based techniques, such as nonnegative matrix factorization and concept factorization, have attracted great attention in dimensionality reduction and data clustering. Previous studies show that both of them yield impressive results on image processing and document clustering. However, both of them are essentially unsupervised methods and cannot incorporate label information. In... View full abstract»

• ### Robust Hashing With Local Models for Approximate Similarity Search

Publication Year: 2014, Page(s):1225 - 1236
Cited by:  Papers (43)
| | PDF (9239 KB) | HTML

Similarity search plays an important role in many applications involving high-dimensional data. Due to the known dimensionality curse, the performance of most existing indexing structures degrades quickly as the feature dimensionality increases. Hashing methods, such as locality sensitive hashing (LSH) and its variants, have been widely used to achieve fast approximate similarity search by trading... View full abstract»

• ### Many-to-Many Superpixel Matching for Robust Tracking

Publication Year: 2014, Page(s):1237 - 1248
Cited by:  Papers (7)
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We present a robust tracking method based on many-to-many image superpixel matching (MMM). Our MMM tracker represents a target and its background using two sets of superpixels. Multiple hypotheses for superpixel matching are considered for better tracking performance. For each superpixel in an input image, k matching candidates are searched in the representative sets using approximate k-NN searchi... View full abstract»

• ### IEEE Systems, Man, and Cybernetics Society Information

Publication Year: 2014, Page(s): C3
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• ### IEEE Transactions on Cybernetics information for authors

Publication Year: 2014, Page(s): C4
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## Aims & Scope

The scope of the IEEE Transactions on Cybernetics includes computational approaches to the field of cybernetics.

Full Aims & Scope

## Meet Our Editors

Editor-in-Chief
Prof. Jun Wang
Dept. of Computer Science
City University of Hong Kong
Kowloon Tong, Kowloon, Hong Kong
Tel: +852 34429701
Email: jwang.cs@cityu.edu.hk